This paper describes work on a framework for multi-agent research using low cost Micro Aerial Vehicles (MAV's). In the past this type of research has required significant investment for both the vehicles themselves and the infrastructure necessary to safely conduct experiments. We present an alternative solution using a robust, low cost, off the shelf platform. We demonstrate the capabilities of our system via two typical multi-robot tasks: obstacle avoidance and exploration. Developing multi-agent applications safely and quickly can be difficult using hardware alone, to address this we also present a multi-quadcopter simulation based around the Gazebo 3D simulator. © 2014 Springer International Publishing.
CITATION STYLE
Williams, R., Konev, B., & Coenen, F. (2014). Multi-agent environment exploration with AR.Drones. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8717 LNAI, pp. 60–71). Springer Verlag. https://doi.org/10.1007/978-3-319-10401-0_6
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